The estimation of traffic matrices in a communications network on the basis of a set of traffic measurements on the network links is a well-known problem, for which a number of solutions have been proposed when the traffic does not show dependence over time, as in the case of the Poisson process. However, extensive measurements campaigns conducted on IP networks have shown that the traffic exhibits long range dependence. Here a method is proposed for the estimation of traffic matrices in the case of long range dependence, and its theoretical properties are studied. Its merits are then evaluated via a simulation study. Finally, an application to real data is provided.

Estimation of traffic matrices in the presence of long memory traffic / Conti, Pier Luigi; DE GIOVANNI, Livia; M., Naldi. - In: STATISTICAL MODELLING. - ISSN 1471-082X. - STAMPA. - 12:1(2012), pp. 29-65. [10.1177/1471082x1001200103]

Estimation of traffic matrices in the presence of long memory traffic

CONTI, Pier Luigi
Methodology
;
2012

Abstract

The estimation of traffic matrices in a communications network on the basis of a set of traffic measurements on the network links is a well-known problem, for which a number of solutions have been proposed when the traffic does not show dependence over time, as in the case of the Poisson process. However, extensive measurements campaigns conducted on IP networks have shown that the traffic exhibits long range dependence. Here a method is proposed for the estimation of traffic matrices in the case of long range dependence, and its theoretical properties are studied. Its merits are then evaluated via a simulation study. Finally, an application to real data is provided.
2012
network tomography; long range dependence; self-similarity; traffic estimation
01 Pubblicazione su rivista::01a Articolo in rivista
Estimation of traffic matrices in the presence of long memory traffic / Conti, Pier Luigi; DE GIOVANNI, Livia; M., Naldi. - In: STATISTICAL MODELLING. - ISSN 1471-082X. - STAMPA. - 12:1(2012), pp. 29-65. [10.1177/1471082x1001200103]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/375871
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